2 citations · 2 across the 4 of their papers we have counts for
5 papers
Replicability of Simulation Studies for the Investigation of Statistical Methods: The RepliSims Project
K. Luijken, A. Lohmann, U. Alter +13
Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is im…
Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation
Linda Nab, Rolf H. H. Groenwold
Sensitivity analysis for measurement error can be applied in the absence of validation data by means of regression calibration and simulation-extrapolation. These have not been com…
mecor: An R package for measurement error correction in linear regression models with a continuous outcome
Linda Nab, Maarten van Smeden, Ruth H. Keogh +1
Measurement error in a covariate or the outcome of regression models is common, but is often ignored, even though measurement error can lead to substantial bias in the estimated co…
Sensitivity analysis for bias due to a misclassfied confounding variable in marginal structural models
Linda Nab, Rolf H. H. Groenwold, Maarten van Smeden +1
In observational research treatment effects, the average treatment effect (ATE) estimator may be biased if a confounding variable is misclassified. We discuss the impact of classif…
Measurement error in continuous endpoints in randomised trials: problems and solutions
Linda Nab, Rolf H. H. Groenwold, Paco M. J. Welsing +1
In randomised trials, continuous endpoints are often measured with some degree of error. This study explores the impact of ignoring measurement error, and proposes methods to impro…